The new Scientific Decade 2013–2022 of IAHS, entitled “Panta Rhei—Everything Flows”, is dedicated to research activities on change in hydrology and society. The purpose of Panta Rhei is to reach an ...improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems. The practical aim is to improve our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment. The concept implies a focus on hydrological systems as a changing interface between environment and society, whose dynamics are essential to determine water security, human safety and development, and to set priorities for environmental management. The Scientific Decade 2013–2022 will devise innovative theoretical blueprints for the representation of processes including change and will focus on advanced monitoring and data analysis techniques. Interdisciplinarity will be sought by increased efforts to connect with the socio-economic sciences and geosciences in general. This paper presents a summary of the Science Plan of Panta Rhei, its targets, research questions and expected outcomes. Editor Z.W. Kundzewicz Citation Montanari, A., Young, G., Savenije, H.H.G., Hughes, D., Wagener, T., Ren, L.L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl, G., Sivapalan, M., Beven, K., Gupta, H., Hipsey, M., Schaefli, B., Arheimer, B., Boegh, E., Schymanski, S.J., Di Baldassarre, G., Yu, B., Hubert, P., Huang, Y., Schumann, A., Post, D., Srinivasan, V., Harman, C., Thompson, S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., and Belyaev, V., 2013. “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022. Hydrological Sciences Journal . 58 (6) 1256–1275.
The hydrology of high mountainous catchments is often predicted with conceptual precipitation-discharge models that simulate the snow accumulation and ablation behavior of a very complex environment ...using as only input temperature and precipitation. It is hereby often assumed that some glacier-wide annual balance estimates, in addition to observed discharge, are sufficient to reliably calibrate such a model. Based on observed data from Rhonegletscher (Switzerland), we show in this paper that information on the seasonal mass balance is a pre-requisite for model calibration. And we present a simple, but promising methodology to include point mass balance observations into a systematic calibration process. The application of this methodology to the Rhonegletscher catchment illustrates that even small samples of point observations do contain extractable information for model calibration. The reproduction of these observed seasonal mass balance data requires, however, a model structure modification, in particular seasonal lapse rates and a separate snow accumulation and rainfall correction factor. This paper shows that a simple conceptual model can be a valuable tool to project the behavior of a glacier catchment but only if there is enough seasonal information to constrain the parameters that directly affect the water mass balance. The presented multi-signal model identification framework and the simple method to calibrate a semi-lumped model on point observations has potential for application in other modeling contexts.
The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments ...to assess the impact of human activities or climate change on riverine fauna over large spatial areas. A comprehensive literature review presented in this study shows that the temperature metrics predicted by the majority of models correspond to yearly aggregates, such as the popular annual maximum weekly mean temperature (MWMT). As a consequence, current models are often unable to predict the annual cycle of stream temperature, nor can the majority of them forecast the inter-annual variation of stream temperature. This study presents a new statistical model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country (Switzerland). Contrary to similar models developed to date, which are mostly based on standard regression approaches, this one attempts to incorporate physical aspects into its structure. It is based on the analytical solution to a simplified version of the energy-balance equation over an entire stream network. Some terms of this solution cannot be readily evaluated at the regional scale due to the lack of appropriate data, and are therefore approximated using classical statistical techniques. This physics-inspired approach presents some advantages: (1) the main model structure is directly obtained from first principles, (2) the spatial extent over which the predictor variables are averaged naturally arises during model development, and (3) most of the regression coefficients can be interpreted from a physical point of view – their values can therefore be constrained to remain within plausible bounds. The evaluation of the model over a new freely available data set shows that the monthly mean stream temperature curve can be reproduced with a root-mean-square error (RMSE) of ±1.3 °C, which is similar in precision to the predictions obtained with a multi-linear regression model. We illustrate through a simple example how the physical aspects contained in the model structure can be used to gain more insight into the stream temperature dynamics at regional scales.
Understanding and predicting bedload transport is an important element of watershed management. Yet, predictions of bedload remain uncertain by up to several order(s) of magnitude. In this ...contribution, we use a 5‐year continuous time series of streamflow and bedload transport monitoring in a 13.4‐km2 snow‐dominated Alpine watershed in the Western Swiss Alps to investigate hydrological drivers of bedload transport. Following a calibration of the bedload sensors, and a quantification of the hydraulic forcing of streamflow upon bedload, a hydrological analysis is performed to identify daily flow hydrographs influenced by different hydrological drivers: rainfall, snowmelt, and combined rain and snowmelt events. We then quantify their respective contribution to bedload transport. Results emphasize the importance of combined rain and snowmelt events, for both annual bedload volumes (77% on average) and peaks in bedload transport rate. A non‐negligible, but smaller, amount of bedload transport may occur during late summer and autumn storms, once the snowmelt contribution and baseflow have significantly decreased (9% of the annual volume on average). Although rainfall‐driven changes in flow hydrographs are responsible for a large majority of the annual bedload volumes (86% on average), the identified melt‐only events also represent a substantial contribution (14% on average). The results of this study help to improve current predictions of bedload transport through a better understanding of the bedload magnitude‐frequency relationship under different hydrological conditions. We further discuss how bedload transport could evolve under a changing climate through its effects on Alpine watershed hydrology.
Plain Language Summary
Understanding and predicting bedload transport is an important element of watershed management. Yet, it remains a challenge to predict bedload transport accurately. In this study, we profit from a rare 5‐year continuous time series of streamflow and bedload transport in a 13.4‐km2 snow‐dominated Alpine watershed in the Western Swiss Alps to investigate the hydrological drivers of bedload transport. An analysis of the streamflow time series together with meteorological data allows classification of daily flow hydrographs over the 5 years of observation between rainfall‐driven, melt‐driven, and a combination of both, and quantification of their contribution with regards to bedload transport. Results of the study show that combined rainfall and snowmelt events with high baseflow are the dominant driver of bedload transport (77% of annual bedload on average), followed to a lower extent by rainfall occurring in the late summer and autumn (9% of annual bedload on average), when the melt contribution and baseflow are lower. The results of this study help to improve current predictions of bedload transport through a better understanding of the bedload magnitude‐frequency relationship under different hydrological conditions. We further discuss how bedload transport could evolve under a changing climate through its effects on Alpine watershed hydrology.
Key Points
The co‐occurrence of rainfall in a watershed where the snowmelt signal is strong was the largely dominant driver of bedload transport
Melt‐only events, and rainfall events occurring once the melt signal has become smaller, were drivers of secondary importance
Combined rain and snowmelt, and melt‐only drivers of bedload transport, may decrease due to climate change impacts on Alpine hydrology
This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely ...gauged river basins, where data is uncertain, intermittent or nonconcomitant. At the heart of this framework is the conditioning of the model parameters such as to reproduce key signatures of the observed data within some limits of acceptability. These signatures are either based on hard or on soft information. Hard information signatures are defined as signatures for which the limits of acceptability may be objectively derived from the distribution of long series of observed values, and which effectively constrain the model parameters. Soft signatures are less effective in parameter conditioning or their limits of acceptability cannot be objectively derived. During random parameter sampling, parameter sets are accepted as equally likely if they meet all the hard limits of acceptability. This results in an intermediate parameter distribution, which can be used to reduce the sampling limits. Then, the soft information may be introduced in a second constraining step to reach a final parameter distribution. The modeler can use the final results as a guideline for a further search for information, possibly from new observations yet to collect. In an application of the framework to the Luangwa catchment in Zambia, three information signatures are retrieved from a data set of old discharge time series and used to condition the parameters of a daily conceptual rainfall‐runoff model. We performed two independent calibration experiments with two significantly different satellite rainfall estimates as model input. The results show consistent parameter distributions and considerable reduction of the prior parameter space and corresponding output realizations. These results illustrate the potential of the proposed calibration framework for predictions in scarcely gauged catchments.
Key Points
Analytic model for the probability distribution of snow‐dominated streamflow
Stochastic framework to link precipitation (rain, snow) and streamflow dynamics
14 case studies confirm ...progress in statistical characterization of streamflow
We propose a novel analytical description of the streamflow probability distribution functions (pdfs) in Alpine catchments characterized by pronounced, snow‐dominated winter low flows. Knowledge about such hydrological regimes is crucial for water resources management in mountain environments and the related wide range of socio‐economic, environmental and ecological services. We use a stochastic framework, generalizing that employed by Botter et al. (2007b), to link precipitation (rain and snow) and streamflow dynamics. The effect of snow dynamics on the flow regime is specifically included by incorporating the temporary disconnection of high‐elevation areas that experience freezing conditions over the entire winter season, and the delay produced on streamflow formation by the temporary accumulation (and later melting) of snow at lower elevations. The novel analytical model employs four parameters that can be directly estimated from observed discharge, precipitation and air temperatures, and one calibration parameter (the elevation threshold
z* delimiting catchment areas with a permanent seasonal snow cover that is nonresponsive during winter owing to snow accumulation without melt). We test the developed model for 14 catchments with contrasting hydroclimatic conditions, located in the Swiss and the Italian Alps. Overall, the proposed analytic model reproduces the observed streamflow pdfs remarkably well. Exceptions exist, though, and the possible origin of deviations between observed and modeled pdfs are discussed. We suggest that our approach marks a progress toward the general statistical characterization of catchment streamflow variability.
This paper presents a spatially explicit model for hydrothermal response simulations of Alpine catchments, accounting for advective and nonadvective energy fluxes in stream networks characterized by ...arbitrary degrees of geomorphological complexity. The relevance of the work stems from the increasing scientific interest concerning the impacts of the warming climate on water resources management and temperature‐controlled ecological processes. The description of the advective energy fluxes is cast in a travel time formulation of water and energy transport, resulting in a closed form solution for water temperature evolution in the soil compartment. The application to Alpine catchments hinges on the boundary conditions provided by the fully distributed and physically based snow model Alpine3D. The performance of the simulations is illustrated by comparing modeled and measured hydrographs and thermographs at the outlet of the Dischma catchment (45 km2) in the Swiss Alps. The Monte Carlo calibration shows that the model is robust and that a simultaneous fitting of streamflow and stream temperature reduces the uncertainty in the hydrological parameters estimation. The calibrated model also provides a good fit to the measurements in the validation period, suggesting that it could be employed for predictive applications, both for hydrological and ecological purposes. The temperature of the subsurface flow, as described by the proposed travel time formulation, proves warmer than the stream temperature during winter and colder during summer. Finally, the spatially explicit results of the model during snowmelt show a notable hydrothermal spatial variability in the river network, owing to the small spatial correlation of infiltration and meteorological forcings in Alpine regions.
Key Points:
Integrated mathematical description of flow and temperature dynamics
Spatially explicit simulations of streamflow and stream temperature
Reliable prediction of seasonal hydro‐thermal cycles in Alpine catchments
Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. ...Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.
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